A tabu search approach for the flow shop scheduling problem

Ben‐Daya, Mohamed; Al-Fawzan, M. A.

doi:10.1016/s0377-2217(97)00136-7

Cited by 137 publications

(45 citation statements)

References 17 publications

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“…Also, Reeves [26] used a genetic algorithm to solve the benchmark problems of Taillard [27] and reported that the simulated annealing algorithm proposed by Osman and Potts [11] performs slightly better than the genetic algorithm. On the other hand, Ben-Daya and Al-Fawzan [16] have proposed a TS-based method, called BF-TS to solve the &ow shop scheduling problem. They used the test problems proposed by Taillard [27] and reported that the BF-TS method performs better than the method proposed by Ogbu and Smith [14] in terms of the quality of solutions.…”

Section: Computational Resultsmentioning

confidence: 99%

“…Turner and Booth [9] and Taillard [10] have veriGed that the method proposed by Nawaz et al [8], namely NEH, performs superior among the constructive methods tested. On the other hand, Osman and Potts [11], Widmer and Hertz [12], Ho and Chang [13], Ogbu and Smith [14], Taillard [10], Nowicki and Smutnicki [15] and Ben-Daya and Al-Fawzan [16] have developed improvement heuristics for the problem of interest.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Several TS-based approaches have been proposed for &ow shop scheduling problem [10,15,16]. Nowicki and Smutnicki [15] used block properties to explore di0erent sequences in &ow shop scheduling.…”

Section: Literature Reviewmentioning

confidence: 99%

See 2 more Smart Citations

A neuro-tabu search heuristic for the flow shop scheduling problem

Solimanpur

Vrat

Shankar

2004

Computers & Operations Research

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Section: Computational Resultsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

A neuro-tabu search heuristic for the flow shop scheduling problem

Solimanpur

Vrat

Shankar

2004

Computers & Operations Research

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“…In our experiments, for the flow shop scheduling problem, firefly and cockroach algorithms are shown to be better than the simulated annealing (SA) but worse than tabu search algorithm (TS) presented in [19] (see Table 3). Comparison of firefly and cockroach algorithms in selected discrete and combinatorial problems 4.2.…”

Section: Comparison Of Firefly and Cockroach Algorithms In Selected Dmentioning

confidence: 89%

“…A comparison of many optimization techniques dedicated to solution of permutation flow shop problem with the makespan criterion can be found in [17]. Due to the complexity of flow shop scheduling, we have good solution techniques, for example Johnson's algorithm for two machine problems, constructive algorithm CDS or NEH [13,18] Many studies describe the tabu search approach in solving the flow shop problem, for example [19][20][21]. Natureinspired metaheuristics were also used to solve the flow shop problem.…”

Section: Optimization By Nature-inspired Metaheuristicsmentioning

confidence: 99%

Comparison of firefly and cockroach algorithms in selected discrete and combinatorial problems

Kwiecień¹,

Filipowicz²

2014

Bulletin of the Polish Academy of Sciences Technical Sciences

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Abstract. In recent years, newer algorithms inspired by nature have been created and used to solve various problems. Therefore, in the paper we present the application of firefly and cockroach algorithms to optimize two queueing systems and permutation flow shop problems with the objective of minimizing the makespan. The article briefly describes these algorithms to solve selected problems and their results. Because these algorithms were originally developed for continuous optimization problems, we introduce a new formula to transform the position of ith individual to solve the discrete problems.

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Efficient scheduling method of complex batch processes with general network structure via agent‐based modeling

2013

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A novel efficient agent-based method for scheduling network batch processes in the process industry is proposed. The agent-based model is based on the resource-task network. To overcome the drawback of localized solutions found in conventional agent-based methods, a new scheduling algorithm is proposed. The algorithm predicts the objective function value by simulating another cloned agent-based model. Global information is obtained, and the solution quality is improved. The solution quality of this approach is validated by detailed comparisons with the mixed-integer programming (MIP) methods. A solution close to the optimal one can be found by the agent-based method with a much shorter computational time than the MIP methods. As a scheduling problem becomes increasingly complicated with increased scale, more specifications, and uncertainties, the advantages of the agent-based method become more evident. The proposed method is applied to simulated industrial problems where the MIP methods require excessive computational resources.A task is selected at the time point of (a) t 1 and (b) t 2 .

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A tabu search approach for the flow shop scheduling problem

Cited by 137 publications

References 17 publications

A neuro-tabu search heuristic for the flow shop scheduling problem

A neuro-tabu search heuristic for the flow shop scheduling problem

Comparison of firefly and cockroach algorithms in selected discrete and combinatorial problems

Efficient scheduling method of complex batch processes with general network structure via agent‐based modeling

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